An iterative method for maximum entropy regularization reconstruction in MRI

Many problems in physics involve imaging objects with high spatial frequenc y content in a limited amount of time. The limitation of available experime ntal data leads to the infamous problem of diffraction limited data, which manifests itself by causing ringing in the image. This ringing is due to in terference phenomena in optics and is known as the Gibbs phenomenon in engi neering. In this paper, an iterative maximum entropy regularization (IMER) algorithm for magnetic resonance imaging (MRI) is developed, which produces a super resolution and optimal signal-to-noise solution to the problem of reconstructing a source from partial Fourier transform data. This method is capable, in principle, of unlimited resolution and is robust with respect to Gaussian white noise perturbation. Comparisons of the IMER method with t he conventional Fourier transform mettled are carried out with the real mag netic resonance data to illustrate the performance of the proposed method. (C) 2000 John Wiley & Sons, Inc.